WO2009114532A2 - Marqueurs permettant de diagnostiquer une inflammation pulmonaire et procédés associés - Google Patents

Marqueurs permettant de diagnostiquer une inflammation pulmonaire et procédés associés Download PDF

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WO2009114532A2
WO2009114532A2 PCT/US2009/036670 US2009036670W WO2009114532A2 WO 2009114532 A2 WO2009114532 A2 WO 2009114532A2 US 2009036670 W US2009036670 W US 2009036670W WO 2009114532 A2 WO2009114532 A2 WO 2009114532A2
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genes
expression
disease
treatment
gene
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WO2009114532A3 (fr
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Milene Saavedra
Jerry Nick
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National Jewish Health
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    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q1/00—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions
    • C12Q1/68—Measuring or testing processes involving enzymes, nucleic acids or microorganisms; Compositions therefor; Processes of preparing such compositions involving nucleic acids
    • C12Q1/6876—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes
    • C12Q1/6883—Nucleic acid products used in the analysis of nucleic acids, e.g. primers or probes for diseases caused by alterations of genetic material
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/106—Pharmacogenomics, i.e. genetic variability in individual responses to drugs and drug metabolism
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/136—Screening for pharmacological compounds
    • C—CHEMISTRY; METALLURGY
    • C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
    • C12Q—MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS; COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
    • C12Q2600/00—Oligonucleotides characterized by their use
    • C12Q2600/158—Expression markers

Definitions

  • the field of the present invention is identification of genetic markers for assessing therapeutic responses in diseases associated with pulmonary inflammation.
  • Cystic fibrosis is the most common lethal inherited disease in the western world. While life expectancies have increased to nearly 40 years, respiratory failure still accounts for >80% of deaths from the disease, usually in young adults in the third or fourth decade of life.
  • FEVi Volume in 1 second or FEVi is the established standard for assessing pulmonary treatment response.
  • FEVi measurements are decreased, treatment is initiated. Following two to three weeks of IV antibiotic therapy, FEVi measurements are typically repeated as a quantitative measure of clinical response. Similarly, FEVi measurements are utilized as the gold standard measurement for treatment response in clinical trials.
  • Airway remodeling driven by inflammatory cells, most directly impacts progressive decline in lung function, and ultimately survival in CF. While novel anti- inflammatory therapies seek to target this decline, fibrosis and remodeling occur slowly and progressively, and may not be detected in a typical month-long Phase 2 trial. Thus, a beneficial effect of an anti-inflammatory treatment, which slows decline in lung function via reduced fibrosis and remodeling, could be missed with monitoring of lung function by FEVl alone.
  • the present invention comprises a method for assessing response to a treatment of a disease that is associated with pulmonary inflammation in a subject, comprising the steps of detecting the expression of one or more genes selected from the group consisting of CD64, ADAM9, CD36, IL32, HPSE, PLXNDl, HCAl 12, CSPG2, TLR2, and CD 163 in a sample taken from the subject before administering the treatment; detecting the expression of one or more genes selected from the group consisting of CD64, ADAM9, CD36, IL32, HPSE, PLXNDl, HCAl 12, CSPG2, TLR2, and CD163 in a sample taken from the subject after administering the treatment; and comparing the level of the expression of the genes from step (a) in the sample taken from the subject before administering the treatment to the level of the expression of the genes from step (b) in the sample taken from the subject after administering the treatment.
  • the present invention comprises detecting the expression of one or more genes from the group consisting of
  • the sample taken from the subject is blood, sputum, bronchoalveolar lavage or urine.
  • the sample comprises cells selected from the group consisting of: leukocytes, lymphocytes, monocytes, basophils, and eosinophils.
  • the disease associated with the pulmonary inflammation is selected from the group consisting of cystic fibrosis, asthma, chronic pulmonary obstructive disease, emphysema, interstitial lung disease, bronchitis, acute respiratory distress syndrome, and pneumonia.
  • the disease is cystic fibrosis lung disease.
  • detecting the expression of genes comprises detection of RNA transcripts of the gene. In some embodiments, detecting the expression of genes comprises detection of the protein encoded by the gene.
  • the present invention comprises a method to identify agents that inhibit the progression of a disease that is associated with pulmonary inflammation, comprising identifying agents that alter the expression or activity of one or more genes selected from the group consisting of CD64, ADAM9, CD36, IL32, HPSE, PLXNDl, HCAl 12, CSPG2, TLR2, and CD163.
  • the disease associated with the pulmonary inflammation is selected from the group consisting of cystic fibrosis, asthma, chronic pulmonary obstructive disease, emphysema, interstitial lung disease, bronchitis, acute respiratory distress syndrome, and pneumonia.
  • the disease is cystic fibrosis lung disease.
  • Figure 1 shows a schematic diagram of the design and execution of the study.
  • Figure 2 shows the comparison of median expression values of the CF gene signature in pre-antibiotic (Pre-Rx) and post-antibiotic (Post-Rx) PBMC samples versus age- and gender-matched normal controls and stable CF controls. Whiskers on boxplots represent range of expression values between patient samples for each individual gene. Median is represented within each box whose boundaries represent 25 th -75 th quartiles. Differences in transcript abundance between pre- versus post- therapy CF patients were significant (p ⁇ 0.05) for all genes, except for HCAl 12.
  • Figure 3 shows the clinical outcomes as represented by changes in FEVi % predicted and CRP pre- and post-antibiotic therapy in the development cohort.
  • FEVi figure represents changes in FEVi% predicted at initiation (Pre-Rx) and termination (Post- Rx) of antibiotics. Boxplot boundaries represent 25 th -75 th quartiles of values, with median line within box, and whiskers representing FEVi% predicted ranges.
  • CRP values in mg/dL are also depicted in pre and post therapy groups, with normal standard range.
  • P 0.02 for differences between FEVi% predicted pre and post therapy, by paired t-test.
  • P O.09 for differences in pre and post therapy CRP values, by paired t-test.
  • FIG 4A and 4B show the Receiver-operating-characteristic ("ROC") curves of gene combinations and FEVi.
  • the present invention relates to novel methods for assessing therapeutic responses in the treatment of a disease that is associated with pulmonary inflammation. These methods are based on the discovery of gene biomarkers whose expression patterns correlate with resolution of pulmonary infection and inflammation.
  • the markers of the present invention represent a novel noninvasive tool to quantify therapeutic responses and to predict resolution of pulmonary exacerbations.
  • the methods of the present invention provide greater sensitivity, specificity and discriminatory capacity than the existing methods that are based on measurements of FEVi alone and when used in conjunction with measurements of
  • FEVi enhance the predictive power of FEVi.
  • pulmonary inflammation and airway inflammation are synonymous and are used interchangeably in this application.
  • the gene expression changes demonstrated reproducibility across two patient groups and discriminatory capacity to differentiate between acutely ill and subsequently treated patients.
  • the regression model described herein demonstrated that the information related to changes in gene expression add meaningful diagnostic information to FEVi in assessing treatment response in acute pulmonary exacerbations.
  • the independent, significant explanatory power contributed by these genes demonstrates that gene expression values from the CF therapeutic signature enhance the predictive discriminating value of FEVi alone.
  • the present invention comprises a group of ten genes (CD64, ADAM9, CD36, IL32, HPSE, PLXNDl, HCAl 12, CSPG2, TLR2, and CD 163) whose expression patterns were found to correlate with resolution of pulmonary infection and inflammation in cystic fibrosis (CF) lung disease.
  • the list of these genes is shown in Table 3b. Seven of the 10 genes and the proteins they encode (IL32, HPSE, ADAM9, PLXNDl, HCAl 12, CSPG2, and CD163) have not previously been linked to CF lung disease.
  • these genes are not specific to CF and have varying roles in other conditions characterized by pathologic pulmonary inflammation, including without limitation, cystic fibrosis, asthma, chronic obstructive pulmonary disease, emphysema, interstitial lung disease, bronchitis, acute respiratory distress syndrome and pneumonia (Wu et al, 2008, Am J Respir Crit Care Med 177(7):720-9; Moller et al, 2006, Crit Care Med 34(10):2561-6).
  • the fact that these genes encode for proteins implicated in inflammatory processes lends biologic plausibility to naming them as potential markers of resolution of CF airway infection and inflammation, as well as other diseases associated with airway infection and inflammation.
  • TLR2 represents a central pattern recognition receptor for the innate response against bacterial infection.
  • IL-32 is a newly described TNF- inducible intracellular cytokine (Kim et al., 2005, Immunity 22(1): 131-42). An inducer of proinflammatory cytokines, IL-32 induces blood monocyte differentiation to macrophages, with subsequent phagocytic activity for live bacteria (Netea et al., 2008, Proc Natl Acad Sci U S A 105(9):3515-20).
  • IL-32 may facilitate differentiation of blood monocytes infiltrating infected lung (Kim et al., 2005, Immunity 22(1): 131-42).
  • Three surface receptor genes participate in phagocytosis. CD64, or Fc ⁇ RIA, mediates receptor mediated endocytosis of IgG-antigen complexes in macrophages (Rodrigo et al., 2006, J Virol 80(20): 10128-3).
  • CD36 a scavenger receptor, mediates macrophage uptake of oxidized LDL, as well as serving as a surface receptor for thrombospondin- 1 (Kwok et al., 2006, Am J Physiol Endocrinol Metab.; Ferreira et al., 2006, Atherosclerosis; Doyen et al., 2003, J Exp Med 198(8): 1277-83).
  • CD163 serves as a macrophage cell surface hemoglobin scavenger receptor, and was recently shown to be highly predictive of mortality in pneumococcal bacteremia (Moller et al., 2006, Crit Care Med 34(10):2561-6; Weiss and Schneider, 2006, Crit Care Med 34(10):2682-3).
  • Degradative enzymes including heparanase, ADAM9 and versican, facilitate extravasation of leukocytes to inflamed tissues. In persistent airway inflammation, this process may culminate in marked and irreversible structural injury to lung parenchyma, by modification of extracellular matrix architecture (Vaday and Lider, 2000, JLeukoc Biol 67(2): 149-59).
  • the study described herein was designed to measure markers that change with aggressive treatment of a pulmonary exacerbation, the current best therapy for reduction of acute increases in airway infection and inflammation in lung diseases.
  • This design had several advantages. First, the design closely paralleled a clinical trial sequence, in which a treatment would be tested for its effect on decreasing inflammation. Second, the gene signature was not pathogen limited. The patient populations used in this study suffered from infection with a representative variety of bacterial pathogens. When patients were treated for pulmonary exacerbations, expression of most of the candidate genes more closely resembled the normal controls (Figure 2), supporting biological roles of these genes as markers of decreased infection and inflammation.
  • ADAM9 One of the genes which added significant explanatory power to the regression model in both patient groups, ADAM9, was highly representative of immediate post-exacerbation transcriptional changes, since its post-exacerbation expression remained significantly different from both normal and stable CF controls.
  • biomarkers have more immediate clinical implications for several large sub-populations of CF patients.
  • airway infection and inflammation can occur as early as four weeks of age (Khan et al., 1995, Am J Respir Crit Care Med 151(4): 1075-82).
  • CT radiographic studies have demonstrated considerable bronchiectasis and parenchymal abnormalities in children with normal lung function (de Jong et al., Eur Respir J 23(l):93-7).
  • Sensitive markers allow for a personalized strategy of anti-infectious and anti-inflammatory treatment in young children, with the ability to rapidly monitor outcomes from these interventions.
  • the present invention comprises a method to assess response to a treatment of a disease that is associated with pulmonary inflammation in a subject.
  • the method includes detecting the expression of one or more genes selected from the group consisting of CD64, ADAM9, CD36, IL32, HPSE, PLXNDl, HCAl 12, CSPG2, TLR2, and CD 163 in a sample taken from the subject before administering the treatment.
  • the method also includes the step of detecting the expression of the selected genes in the sample taken from the subject after administering the treatment.
  • the method also includes comparing the expression levels of the genes before administering the treatment to the expression levels after administering the treatment.
  • the method includes detecting the expression of one or more genes selected from CD64, ADAM9, CD36 and TLR2.
  • the method of the present invention further comprises measuring FEVi in the subject.
  • the methods of the present invention can be used to assess therapeutic responses in the treatment of any disease that is associated with pulmonary inflammation.
  • the diseases contemplated herein include, without limitation, cystic fibrosis, asthma, chronic obstructive pulmonary disease, emphysema, interstitial lung disease, bronchitis, acute respiratory distress syndrome and pneumonia.
  • the disease is cystic fibrosis.
  • a patient sample can include any bodily fluid or tissue from a patient that may contain the RNA or protein encoded by the genes contemplated here.
  • sample or "patient sample” can be used generally to refer to a sample of any type which contains products that are to be evaluated by the present method, including but not limited to, a sample of isolated cells, a tissue sample and/or a bodily fluid sample.
  • a sample of isolated cells is a specimen of cells, typically in suspension or separated from connective tissue which may have connected the cells within a tissue in vivo, which have been collected from an organ, tissue or fluid by any suitable method which results in the collection of a suitable number of cells for evaluation by the method of the present invention.
  • the cells in the cell sample are not necessarily of the same type, although purification methods can be used to enrich for the type of cells that are preferably evaluated.
  • Cells can be obtained, for example, by scraping of a tissue, processing of a tissue sample to release individual cells, or isolation from a bodily fluid.
  • the sample may comprise blood, sputum, bronchoalveolar lavage or urine.
  • the patient sample comprises blood.
  • the sample may comprise Peripheral Blood Mononuclear
  • PBMCs PBMCs
  • leuokocytes monocytes
  • lymphocytes lymphocytes
  • basophils or eosinophils.
  • a systemic marker of lung inflammation has many advantages, as blood can be obtained from subjects of any age and disease severity, and may reflect the status of inflammation throughout the lung, rather than one segment. This analysis is sensitive, inexpensive, and obtained from tissue that is easily accessible in pediatric and adult populations, and has the potential to be performed in a clinical laboratory.
  • the term "expression”, when used in connection with detecting the expression of a gene, can refer to detecting transcription of the gene (i.e., detecting mRNA levels) and/or to detecting translation of the gene (detecting the protein produced).
  • To detect expression of a gene refers to the act of actively determining whether a gene is expressed or not. This can include determining whether the gene expression is upregulated as compared to a control, downregulated as compared to a control, or unchanged as compared to a control. Therefore, the step of detecting expression does not require that expression of the gene actually is upregulated or downregulated, but rather, can also include detecting that the expression of the gene has not changed (i.e., detecting no expression of the gene or no change in expression of the gene).
  • RNA expression is measured by any of a variety of known methods in the art.
  • methods include but are not limited to: extraction of cellular mRNA and Northern blotting using labeled probes that hybridize to transcripts encoding all or part of the gene; amplification of mRNA using gene-specific primers, polymerase chain reaction (PCR), and reverse transcriptase-polymerase chain reaction (RT- PCR), followed by quantitative detection of the product by any of a variety of means; extraction of total RNA from the cells, which is then labeled and used to probe cDNAs or oligonucleotides encoding the gene on any of a variety of surfaces; in situ hybridization; and detection of a reporter gene.
  • PCR polymerase chain reaction
  • RT-PCR reverse transcriptase-polymerase chain reaction
  • Methods to measure protein expression levels generally include, but are not limited to: Western blot, immunoblot, enzyme-linked immunosorbant assay (ELISA), radioimmunoassay (RIA), immunoprecipitation, surface plasmon resonance, chemiluminescence, fluorescent polarization, phosphorescence, immunohistochemical analysis, matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry, microcytometry, microarray, microscopy, fluorescence activated cell sorting (FACS), and flow cytometry, as well as assays based on a property of the protein including but not limited to enzymatic activity or interaction with other protein partners. Binding assays are also well known in the art.
  • a BIAcore machine can be used to determine the binding constant of a complex between two proteins.
  • the dissociation constant for the complex can be determined by monitoring changes in the refractive index with respect to time as buffer is passed over the chip (O'Shannessy et al., 1993, Anal. Biochem. 212:457; Schuster et al., 1993, Nature 365:343).
  • suitable assays for measuring the binding of one protein to another include, for example, immunoassays such as enzyme linked immunoabsorbent assays (ELISA) and radioimmunoassays (RIA); or determination of binding by monitoring the change in the spectroscopic or optical properties of the proteins through fluorescence, UV absorption, circular dichroism, or nuclear magnetic resonance (NMR).
  • ELISA enzyme linked immunoabsorbent assays
  • RIA radioimmunoassays
  • a preferred method is an immunoassay, wherein an A 2A -specific antibody (an antibody that selectively binds to A 2A ) is used to detect the expression on tumor cells.
  • a patient sample can include any bodily fluid or tissue from a patient that may contain tumor cells or proteins of tumor cells. More specifically, according to the present invention, the term "test sample” or “patient sample” can be used generally to refer to a sample of any type which contains cells or products that have been secreted from cells to be evaluated by the present method, including but not limited to, a sample of isolated cells, a tissue sample and/or a bodily fluid sample. According to the present invention, a sample of isolated cells is a specimen of cells, typically in suspension or separated from connective tissue which may have connected the cells within a tissue in vivo, which have been collected from an organ, tissue or fluid by any suitable method which results in the collection of a suitable number of cells for evaluation by the method of the present invention.
  • the cells in the cell sample are not necessarily of the same type, although purification methods can be used to enrich for the type of cells that are preferably evaluated.
  • Cells can be obtained, for example, by scraping of a tissue, processing of a tissue sample to release individual cells, or isolation from a bodily fluid.
  • the present invention includes a method to identify agents that inhibit the progression of a disease that is associated with pulmonary inflammation, comprising identifying agents that alter the expression or activity of one or more genes selected from the group consisting of CD64, ADAM9, CD36, IL32, HPSE, PLXNDl, HCAl 12, CSPG2, TLR2, and CD163.
  • the diseases contemplated herein include, without limitation, cystic fibrosis, asthma, chronic obstructive pulmonary disease, emphysema, interstitial lung disease, bronchitis, acute respiratory distress syndrome and pneumonia.
  • the disease is cystic fibrosis.
  • Example 1 This example illustrates the overall design and step-wise execution of the study described herein.
  • PBMCs Peripheral blood mononuclear cells
  • Gene expression profiling was performed by utilizing gene microarray technique to identify genes whose expression significantly changed with treatment. Thus, candidate gene markers, differentially regulated before and after antibiotic therapy were identified. These genes were independently confirmed in the same set of samples, utilizing quantitative RT-
  • ROC logistic regression/receiver operating characteristic
  • Table 1 summarizes measurement distributions performed for all 24 CF patient samples, including 10 from the Development Cohort and 14 from the Validation Cohort.
  • Example 2 This example describes the initial study performed with patients in the Development Cohort for identification of the genetic markers.
  • Patient recruitment was done as follows. Subjects >18 years of age with CF (based on sweat chloride testing and genotype) were enrolled at the time of admission or home IV antibiotic initiation for a clinically diagnosed pulmonary exacerbation at a large Cystic Fibrosis Foundation accredited adult CF clinic, following obtainment of informed consent from the study subject. All study participants were monitored by the National Jewish Health and University of Colorado Institutional Review Boards. Patients identified for enrollment met CF Foundation Clinical Practice Guidelines of at least 3 of 11 criteria for an acute pulmonary exacerbation (Foundation, C. F. Clinical Practice Guidelines for Cystic Fibrosis).
  • PBMC isolation was performed as follows. Four ml of peripheral blood was collected into sodium citrate tubes (BD Vacutainer® CPTTM, BD Biosciences, Franklin Lakes, NJ) utilizing a Ficoll Hypaque density gradient. PBMCs were isolated via density gradient centrifugation (1650 RCF, 30 minutes, 18 0 C). Furthermore, cytospins with H&E staining verified that all cells from which RNA was extracted were mononuclear and fewer than 1% neutrophils were identified from the interphase.
  • sodium citrate tubes BD Vacutainer® CPTTM, BD Biosciences, Franklin Lakes, NJ
  • PBMC RNA isolated from the development cohort containing 10 patients representing 10 pulmonary exacerbations, was utilized for microarray analysis, in order to identify PBMC transcriptional changes before and after antibiotic therapy. All raw microarray data is available on the NCBI Gene Expression Omnibus Database. Prior to microarray, all RNA was evaluated with an Agilent 2100 Bioanalyzer to confirm high grade RNA quality. PBMC gene expression analysis was performed with HuI 33 Plus 2.0 gene chips. Samples were prepared for Affymetrix arrays using 2.5 ⁇ g of total RNA. First and second strand complimentary DNA was synthesized using standard techniques. Biotin-labeled antisense complimentary RNA was produced by an in vitro transcription reaction.
  • Target hybridization, washing, staining, and scanning probe arrays were done following manufacturer's protocol as described in the Affymetrix GeneChip Expression Analysis Manual.
  • Affymetrix CEL files were loaded into dChip 2005 array analysis software (Li C, Wong WH 2001), normalized to median brightness, and expression modeled using the perfect match/mismatch (PM/MM) algorithm.
  • PBMC microarray data from 8 normal and 6 stable CF matched controls was utilized to assess baseline transcripts of the gene signature. Relationships between CF pre- and post-antibiotic genes, normal and stable CF PBMC controls were evaluated with ANOVA, with post-hoc testing determined by Fisher's PLSD (StatView, SAS Institute Inc., Cary, NC). Statistical significance was assigned for p-values ⁇ 0.05.
  • Microarray expression data from 19 genes in the development cohort were secondarily confirmed by real-time polymerase chain reaction (RT-PCR), utilizing all sufficient remaining RNA for analysis (6 of 10 total patients had sufficient RNA from both pre- and post- therapy PBMC RNA samples).
  • First strand cDNA was made from 1 ⁇ g total RNA using a QuantiTect Reverse Transcription Kit (Qiagen, Valencia, CA). Quantitative real-time PCR was performed using a total reaction volume of 25 ⁇ l, containing 5 ⁇ l of diluted cDNA, 10 ⁇ l H20, 9.94 ⁇ l of the fluorescent indicator Sybrgreen® and 0.03 ⁇ l of each nucleotide primer (250 ⁇ M).
  • PCR was carried out in a 7300 Real Time PCR System (Applied Biosystems, Foster City, CA), using 40 cycles of 95° C for 15 seconds, followed by 60° C for 1 minute, with a 10 minute 95° C initial soak. Each measurement was made in triplicate and expressed relative to the detection of the housekeeping gene, hypoxanthine guanine phosphoribosyl transferase (HPRT). For quantitative RT-PCR, statistics were performed in StatView (SAS, Cary, NC), utilizing paired t-tests, and significance at P ⁇ 0.05.
  • Figure 2 shows the comparison between pre- and post- antibiotic therapy median values and distribution for CF genes in the development cohort, to array data from eight age- and gender-matched normal controls, as well as six stable CF controls.
  • expression of all genes, except for TLR2 significantly differed from expression in normals (ANOVA, p ⁇ 0.05; pairwise comparison with Fisher's PLSD, p ⁇ 0.05) and expression of 5 of 10 genes (PLXNDl, ADAM9, CSPG2, CD64 and CD36) differed from stable CF (ANOVA, p ⁇ 0.05; pairwise comparison with Fisher's PLSD, p ⁇ 0.05).
  • ANOVA p ⁇ 0.05
  • pairwise comparison with Fisher's PLSD p ⁇ 0.05
  • CRP C-reactive protein
  • cytokines were measured in the aliquots of plasma taken from the same blood specimens from which PBMCs were isolated before and after antibiotic therapy. The cytokine measurements were performed as follows. Plasma collected at the time of PBMC isolation was processed at The Children's Hospital, University of Colorado GCRC Core laboratory.
  • cytokine measurements were done using the Fluorokine® MAP Cytokine assay (R&D systems, Minneapolis, MN) on the Luminex 100 system (a dual laser, flow-based sorting and detection platform) to quantify the following cytokines at each blood draw: IL- l ⁇ , IL-I ⁇ , IL-IRA, IL-2, IL-4, IL-5, IL-6, IL-8, IL-10, IL-17, TNF ⁇ , IFN ⁇ , G- CSF, GM-CSF, MIP- l ⁇ , MCP-I, VEGF, RANTES, and IL- 13. All analyses were performed according to manufacturer's protocols.
  • the mean minimal detectable doses for cytokines are as follows: IL-Ig (0.39 pg/ml), IL- l ⁇ , (0.27 pg/ml), IL- Ira (2.06 pg/ml), IL- 2 (0.89 pg/ml), IL-4, (1.75 pg/ml), IL-5 (0.33 pg/ml), IL-6 (0.36 pg/ml), IL-8 (0.39 pg/ml), IL-10 (0.13 pg/ml), IL-17 (0.39 pg/ml), TNFg (0.47pg/ml), IFN ⁇ (0.3 lpg/ml), G-CSF (0.57 pg/ml), GM-CSF (1.05pg/ml), MTP-I ⁇ ⁇ 2.12 pg/ml ., MCP-I (0.95 pg/ml), VEGF (0.81 pg/m
  • the primary endpoints of the study were lung function (FEVi) and gene transcript abundance changes after treatment of an acute pulmonary exacerbation. All patients were evaluated with testing as described above as well as clinical evaluation at the onset and completion of therapy. Patients who responded to therapy by manifesting improvement in FEVi % predicted at the completion of antibiotic therapy and not requiring rehospitalization within 1 week with a diagnosis of pulmonary exacerbation were analyzed such that changes in FEVi% predicted were regressed with transcript changes. Pulmonary function testing was performed in compliance with American Thoracic Society standards [E4]. The statistical methods used in the study were as follows. Comparison of gene expression values pre- and post- antibiotic therapy were initially performed by paired univariate analyses: t test and the Wilcoxon signed rank test. Validation study
  • Example 3 This example illustrates the diagnostic value of the CF therapeutic signature in association with % change in FEVi and demonstrates that the gene expression values from the CF therapeutic signature enhance the predictive discriminating value of FEVi alone.
  • ROC receiver operating characteristic
  • ROC curves demonstrated the sensitivity and specificity of gene expression values for assessing treatment response.
  • Juxtaposition of ROC curves demonstrated the additional discriminatory capacity of gene measurements in comparison to FEV 1 alone, to diagnose resolution of airway inflammation.

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Abstract

La présente invention concerne la récente découverte d'un nombre de gènes qui ont été identifiés comme marqueurs systémiques d'une inflammation pulmonaire. Cette découverte permet la mise au point d'un nouvel outil pour évaluer des réponses thérapeutiques d’une manière fiable, rapide, et efficace. Elle permet également la mise au point de thérapies innovantes dirigées contre des maladies associées à une inflammation pulmonaire. Dans un mode de réalisation, la présente invention permet de quantifier une réponse thérapeutique chez des patients atteints d'une maladie associée à une inflammation pulmonaire. Dans des modes de réalisation préférés, les gènes sont les suivants : CD64, ADAM9, CD36, IL32, HPSE, PLXND1, HCA112, CSPG2, TLR2, et CD163.
PCT/US2009/036670 2008-03-10 2009-03-10 Marqueurs permettant de diagnostiquer une inflammation pulmonaire et procédés associés WO2009114532A2 (fr)

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US20090233300A1 (en) 2009-09-17
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US20160068909A1 (en) 2016-03-10

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